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Ch4

Databases🔗

Amazon DynamoDB🔗

  • NoSQL Database (Key-Value Store) : A collection of items or records.
  • You can look up data :
    • Using a primary key for each item
    • Through the use of indexes
  • Very High Performance mainly used for Gaming, Web, Mobile and IoT
  • Fully Managed : backups, patches etc are managed by AWS
  • Bill consists of two factors
    • The total amount of throughput that you configure for your tables (provisioned capacity )
    • The total amount of storage space used by your data
  • DynamoDB tables are schemaless, schema is defined per item
    • As long as the primary key is valid there is no limit on attributes
    • primary key consists of two attributes : partition key and sort key
  • You can define several secondary indexes besides primary key for search
    • There are two types of secondary indexes : Global and Local Indexes
  • Disadvantages
    • Since replication of data is present thorough multiple zones so it relies on concept of Eventual Consistency, so its possible some zones might have older data
    • Queries are less flexible than SQL
    • Strict Workflow limitations like max record size : 400kb, max indexes per table : 20 global, 5 local
    • provisioned throughput (ProvisionedThroughputExceededException)

Amazon Relational Database Service (RDS)🔗

  • Its a fully managed RDS that allows users to Provision, Create, Scale a relation database
  • RDS allows us to choose from various Database Engines : MySQL, MariaDB, PostgreSQL, Amazon Aurora (fork of MySQL), Oracle (Common in Corporate), SQL Server
  • Choice of compute instances is available while provisioning Database
    • General Purpose
    • Memory Optimized
  • Synchrous Replication between primary and secondary instance. In case if primary instance fails then AWS automatically points DNS to secondary instance within (60-120s). [Multi AZ]
  • Storage Autoscaling
    • EBS (Elastic Block Storage) (MySQL, Postgres, MariaDB, Oracle, SQL server)
      • General Purpose SSD storage, good for broad range of cases
      • Provisioned IOPS (SSD Storage), good for workloads that operate at very hight I/O
      • Magnetic Storage (mostly for backwards compatibility)
    • Shared Cluster Storage (Amazon Aurora)
      • Configuration options doesn’t exists and scaling occurs automatically
  • vertical scaling : scaling towards computing capability
  • horizontal scaling : increasing replicas of storage instances to deal with high volume of read queries. Note all replicas are synchrously linked.

Amazon ElastiCache🔗

  • This service improves performance by using caching, where web application allow you to retrieve information fast, managed, in-memory data stores.
  • Caching : Additional memory enables our devices to store frequently accessed information in memory instead of having to request the information from the hard drive
  • It improves the read-only performance of server.
  • Engines
    • Amazon Elasticache for Memcached : A high performance, submillisecond latency Memcached Compatible in-memory, key-value store service that can either be used as a cache, in addition to a data store
    • Amazon Elasticache for Redis : An in-memory data store designed for high performance and again providing sub-millisecond latency on a huge scale to real-time applications
  • Components of Elasticode
    • Node : a fixed sized chunk of secure network attached RAM
    • Shard : redis shard (node group) a group of up to 6 Elasticache nodes
    • Redis Cluster : group of 1-90 redis shards
    • Memcached Cluster : a collection of more cache nodes
  • Elasticache should never used
    • when data persistence is necessary
    • when working with primary data records
    • when we need write performance, rather than read performance